Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints

Understand

We present Attract-Repel, an algorithm for improving the semantic quality of word vectors by injecting constraints extracted from lexical resources.

• Attract-Repel facilitates the use of constraints from mono- and cross-lingual resources, yielding semantically specialised cross-lingual vector spaces.
• Our evaluation shows that the method can make use of existing cross-lingual lexicons to construct high-quality vector spaces for a plethora of different languages, facilitating semantic transfer from high- to lower-resource ones.
• The effectiveness of our approach is demonstrated with state-of-the-art results on semantic similarity datasets in six languages.